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    • 31. 发明授权
    • Rule-based segmentation for objects with frontal view in color images
    • 在彩色图像中具有正面视图的对象的基于规则的分割
    • US08682029B2
    • 2014-03-25
    • US12735093
    • 2008-12-12
    • Robinson Piramuthu
    • Robinson Piramuthu
    • G06K9/00
    • G06K9/00234G06T7/11G06T2207/30196G06T2207/30201
    • A method of labeling pixels in an image that represent human skin are detected and one or more regions in the image are identified. Each region may include all or a portion of a human face. Pixels that represent each face in the image are identified using the pixels that represent skin and the regions that include faces of the people, thereby identifying a position of each face in the image. A face mask and a torso map corresponding to each face is determined using determined face positions. The extracted face masks and the torso maps are used to refine a skin map. A person or people map is determined using the skin map and the rough body map.
    • 检测表示人体皮肤的图像中的像素的方法,并且识别图像中的一个或多个区域。 每个区域可以包括人脸的全部或一部分。 使用表示皮肤的像素和包括人脸的区域来识别代表图像中每个面部的像素,从而识别图像中每个面部的位置。 使用确定的脸部位置来确定对应于每个脸部的面罩和躯干图。 提取的面罩和躯干图用于细化皮肤图。 使用皮肤图和粗体图确定人物或人物图。
    • 32. 发明申请
    • Systems and methods for manifold learning for matting
    • 用于消光的歧管学习的系统和方法
    • US20110274344A1
    • 2011-11-10
    • US13068460
    • 2011-05-10
    • Kuang-chih LeeRobinson Piramuthu
    • Kuang-chih LeeRobinson Piramuthu
    • G06K9/62
    • G06K9/6252G06T7/11G06T7/143G06T7/194
    • Systems for manifold learning for matting are disclosed, with methods and processes for making and using the same. The embodiments disclosed herein provide a closed form solution for solving the matting problem by a manifold learning technique, Local Linear Embedding. The transition from foreground to background is characterized by color and texture variations, which should be captured in the alpha map. This intuition implies that neighborhood relationship in the feature space should be preserved in the alpha map. By applying Local Linear Embedding using the disclosed embodiments, the local image variations can be preserved in the embedded manifold, which is the resulting alpha map. Without any strong assumption, such as color line model, the disclosed embodiments can be easily extended to incorporate other features beyond RGB color features, such as gradient and texture information.
    • 公开了用于消光的流体学习系统,其具有用于制造和使用其的方法和过程。 本文公开的实施例提供了一种用于通过歧管学习技术局部线性嵌入来解决消光问题的闭合形式解决方案。 从前景到背景的转换的特点是颜色和纹理变化,应该在alpha图中捕获。 这种直觉意味着特征空间中的邻域关系应该保留在alpha图中。 通过使用所公开的实施例应用局部线性嵌入,局部图像变化可以保留在嵌入式多维数据集中,这是所得到的α图。 没有任何强烈的假设,例如颜色线模型,所公开的实施例可以容易地扩展以包含超出RGB颜色特征(诸如梯度和纹理信息)的其他特征。
    • 35. 发明授权
    • Process excursion detection
    • 过程偏移检测
    • US08289510B2
    • 2012-10-16
    • US13024471
    • 2011-02-10
    • Patrick Y. HuetRobinson PiramuthuMartin PlihalChristopher W. LeeCho H. TehYan Xiong
    • Patrick Y. HuetRobinson PiramuthuMartin PlihalChristopher W. LeeCho H. TehYan Xiong
    • G01N21/00
    • G01N21/8851G01N21/9501G01N2021/8854G01N2021/8864G06T7/0004G06T2207/30148
    • A method for analyzing defect information on a substrate, including logically dividing the substrate into zones, and detecting defects on the substrate to produce the defect information. The defect information from the substrate is analyzed on a zone by zone basis to produce defect level classifications for the defects within each zone. The zonal defect level classifications are analyzed according to at least one analysis method. The defect level classifications are preferably selected from a group of defect level classifications that is specified by a recipe. Preferably, the at least one analysis method includes at least one of zonal defect distribution, automatic defect classification, spatial signature analysis, and excursion detection. The defect level classifications preferably include at least one of individual defect, defect cluster, and spatial signature analysis signature. In one embodiment the defect information is logically divided into configurable zones after the defects on the substrate have been detected.
    • 一种用于分析衬底上的缺陷信息的方法,包括将衬底逻辑划分为区域,以及检测衬底上的缺陷以产生缺陷信息。 在逐个区域的基础上分析来自基板的缺陷信息,以产生每个区域内的缺陷的缺陷水平分类。 根据至少一种分析方法分析区域缺陷水平分类。 缺陷级分类优选地从由食谱指定的一组缺陷级别分类中选择。 优选地,所述至少一个分析方法包括区域缺陷分布,自动缺陷分类,空间签名分析和偏移检测中的至少一个。 缺陷级分类优选地包括个体缺陷,缺陷簇和空间签名分析签名中的至少一个。 在一个实施例中,在检测到衬底上的缺陷之后,将缺陷信息在逻辑上划分为可配置区域。
    • 37. 发明申请
    • Systems and methods for segmenting human hairs and faces in color images
    • 用于将人的头发和脸部分割成彩色图像的系统和方法
    • US20110299776A1
    • 2011-12-08
    • US13066112
    • 2011-04-05
    • Kuang-chih LeeRobinson PiramuthuKatharine IpDaniel Prochazka
    • Kuang-chih LeeRobinson PiramuthuKatharine IpDaniel Prochazka
    • G06K9/34
    • G06K9/00281G06K9/00234G06K9/46
    • Systems for segmenting human hairs and faces in color images are disclosed, with methods and processes for making and using the same. The image may be cropped around the face area and roughly centered. Optionally, the illumination environment of the input image may be determined. If the image is taken under dark environment or the contrast between the face and hair regions and background is low, an extra image enhancement may be applied. Sub-processes for identifying the pose angle and chin contours may be performed. A preliminary mask for the face by using multiple cues, such as skin color, pose angle, face shape and contour information can be represented. An initial hair mask by using the abovementioned multiple cues plus texture and hair shape information may be created. The preliminary face and hair masks are globally refined using multiple techniques.
    • 公开了用于分割彩色图像中的人发和脸部的系统,其具有用于制造和使用它们的方法和过程。 图像可能会在脸部区域周围裁剪,并且大致居中。 可选地,可以确定输入图像的照明环境。 如果在黑暗环境下拍摄图像,或者脸部和头发区域与背景之间的对比度较低,则可能会应用额外的图像增强。 可以执行用于识别姿态角度和下巴轮廓的子过程。 可以表示通过使用多种线索(如肤色,姿态角度,脸部形状和轮廓信息)的面部的初步面具。 可以创建通过使用上述多重线索加上纹理和头发形状信息的初始头发面罩。 初步的面部和头发面罩使用多种技术进行全球精炼。
    • 38. 发明申请
    • SYSTEM AND METHOD FOR SEGMENTATION OF AN IMAGE INTO TUNED MULTI-SCALED REGIONS
    • 将图像分割成多个调制区域的系统和方法
    • US20100008576A1
    • 2010-01-14
    • US12502125
    • 2009-07-13
    • Robinson Piramuthu
    • Robinson Piramuthu
    • G06K9/34
    • G06K9/342G06T7/11G06T7/155G06T2207/20152
    • Systems and methods for segmentation of an image into tuned multi-scale regions that comprise similarity in the pixels contained in each respective region. A watershed transform sub-process is performed upon an edge strength map of the image. A process for deriving an edge strength map may comprise preprocessing the image, extracting channels from the image, applying an edge operator to each channel, enhancing edge signal, normalizing the edge channels, combining the edge channels, and enhancing the signal to noise ratio for the channel. Once the watershed transform is complete, decisions on which neighboring regions to agglomerate may occur based on the cost effectiveness of the mergers. As desired, the boundaries for the regions created are resolved.
    • 用于将图像分割成包括每个相应区域中包含的像素中的相似性的调谐多尺度区域的系统和方法。 在图像的边缘强度图上执行分水岭变换子过程。 用于导出边缘强度图的过程可以包括对图像进行预处理,从图像中提取频道,向每个信道应用边缘算子,增强边缘信号,归一化边缘信道,组合边缘信道,以及增强信噪比 这个频道。 一旦分水岭变化完成,根据合并的成本效益,可能发生哪些邻近地区聚集的决定。 根据需要,解决了创建的区域的边界。
    • 39. 发明申请
    • Process Excursion Detection
    • 过程偏移检测
    • US20080204739A1
    • 2008-08-28
    • US12117823
    • 2008-05-09
    • Patrick Y. HuetRobinson PiramuthuMartin PlihalChristopher W. LeeCho H. TehYan Xiong
    • Patrick Y. HuetRobinson PiramuthuMartin PlihalChristopher W. LeeCho H. TehYan Xiong
    • G01N21/88
    • G01N21/8851G01N21/9501G01N2021/8854G01N2021/8864G06T7/0004G06T2207/30148
    • A method for analyzing defect information on a substrate, including logically dividing the substrate into zones, and detecting defects on the substrate to produce the defect information. The defect information from the substrate is analyzed on a zone by zone basis to produce defect level classifications for the defects within each zone. The zonal defect level classifications are analyzed according to at least one analysis method. The defect level classifications are preferably selected from a group of defect level classifications that is specified by a recipe. Preferably, the at least one analysis method includes at least one of zonal defect distribution, automatic defect classification, spatial signature analysis, and excursion detection. The defect level classifications preferably include at least one of individual defect, defect cluster, and spatial signature analysis signature. In one embodiment the defect information is logically divided into configurable zones after the defects on the substrate have been detected.
    • 一种用于分析衬底上的缺陷信息的方法,包括将衬底逻辑划分为区域,以及检测衬底上的缺陷以产生缺陷信息。 在逐个区域的基础上分析来自基板的缺陷信息,以产生每个区域内的缺陷的缺陷水平分类。 根据至少一种分析方法分析区域缺陷水平分类。 缺陷级分类优选地从由食谱指定的一组缺陷级别分类中选择。 优选地,所述至少一个分析方法包括区域缺陷分布,自动缺陷分类,空间签名分析和偏移检测中的至少一个。 缺陷级分类优选地包括个体缺陷,缺陷簇和空间签名分析签名中的至少一个。 在一个实施例中,在检测到衬底上的缺陷之后,将缺陷信息在逻辑上划分为可配置区域。